[FIXED] How to detect up and down trend in a list

Issue

A lot of python list with some data, how to detect the data in the list is meet downward then upward. For example:

a1 = [8,6,4,1,-2,-6,5,8,9,87] 
a2 = [8,6,4,1,-2,-6,5,-8,9,10]

where data in a1 is downard then upward,expect print 'OK' but data in a2 is downard then upward then downard last upward, expect print 'NG' how to do it by python?

Solution

You can compute the sign of the successive differences, then only keep the different ones. If this yields [-1, 1] this is a OK, else a NG:

import numpy as np

def check(lst):
    # sign of successive difference
    s = np.sign(np.diff(lst))
    # mask to deduplicate successive values
    m1 = np.r_[True, s[:-1]!=s[1:]]
    # mask to remove flat lines
    m2 = s != 0
    # OK if both masks are True else NG
    return 'OK' if s[m1&m2].tolist() == [-1, 1] else 'NG'

check(a1)
# 'OK'

check(a2)
# 'NG'

check([2,1,1,2])
# 'OK'

Intermediates:

### first example

lst
# [8, 6, 4, 1, -2, -6, 5, 8, 9, 87]

s = np.sign(np.diff(lst))
# array([-1, -1, -1, -1, -1,  1,  1,  1,  1])

s[np.r_[True, s[:-1]!=s[1:]]].tolist()
# [-1, 1]

### second example

lst
# [8, 6, 4, 1, -2, -6, 5, -8, 9, 10]

s = np.sign(np.diff(lst))
# array([-1, -1, -1, -1, -1,  1, -1,  1,  1])

s[np.r_[True, s[:-1]!=s[1:]]].tolist()
# [-1, 1, -1, 1]

Answered By - mozway